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United States health expenditures continue to escalate at unsustainable rates. A recent movement around increasing price transparency has been suggested as a way of reducing the rate of increase in expenditures, with legislative efforts taking place at both the state and federal level. While this seems on the surface like a good idea, simply providing information on prices to physicians, particularly trainees, may not achieve the type of large changes in practice patterns that proponents expect. The manner in which price transparency is implemented will likely play a significant role in its effectiveness as an intervention. In this article, the authors review efforts of transparency and default options from other contexts and leverage insights from behavioral economics to provide recommendations for increasing the likelihood that price transparency will lead to physicians weighing the relative value of interventions.

Purpose. The biggest challenge for corporate wellness initiatives is low rates of employee participation. We test whether a behavioral economic approach to incentive design (i.e., a lottery) is more effective than a direct economic payment of equivalent monetary value (i.e., a grocery gift certificate) in encouraging employees to complete health risk assessments (HRAs). Design. Employees were assigned to one of three arms. Assignment to a treatment arm versus the nontreatment arm was determined by management. Assignment to an arm among those eligible for treatment was randomized by office. Setting. A large health care management and information technology consulting company. Patients. A total of 1299 employees across 14 offices participated. Intervention. All employees were eligible to receive $25 for completing the HRA. Those in the lottery condition were assigned to teams of four to eight people and, conditional on HRA completion, were entered into a lottery with a prize of $100 (expected value, $25) and a bonus value of an additional $25 if 80% of team members participated. Those in the grocery gift certificate condition who completed an HRA received a $25 grocery gift certificate. Those in the comparison condition received no additional incentive. Measures. HRA completion rates. Analysis. Logistic regression analysis. Results. HRA completion rates were significantly higher among participations in the lottery incentive condition (64%) than in both the grocery gift certificate condition (44%) and the comparison condition (40%). Effects were larger for lower-income employees, as indicated by a significant interaction between income and the lottery incentive. Conclusion. Lottery incentives that incorporate regret aversion and social pressure can provide higher impact for the same amount of money as simple economic incentives.

As more than 40 states face present and projected deficits in their health care budgets, some legislatures are considering market-based reforms to control rising health care costs. This continues a trend begun in the 1990s that emphasized market competition over state regulation and mandates. However, little is known about the impact of many market-based reforms on quality of care. This Issue Brief evaluates the effect of one reform—the deregulation of hospital reimbursement rates in New Jersey—on one important outcome of care—mortality from acute myocardial infarction (heart attack). The findings serve as a reminder that cost-constraining reforms may reduce the quality of care, particularly for uninsured and other vulnerable populations.

Purpose. To examine why high-risk individuals targeted for a telephone care management program participated at low rates. Design. Study design consisted of qualitative, semistructured interviews. Setting. The setting was a large national insurer's telephone-based care management program. The program employed registered nurses to provide individually tailored education and counseling about health and health care. Subjects. Study subjects comprised members of a national insurer who were recruited to participate in a care management program but had either dropped out of the program after a short period of initial engagement or had never participated despite recruitment efforts. Measures. Interview content was divided into four categories: knowledge of the case management program, barriers to program participation, perceptions of benefits of the program, and suggestions for program improvement. Analysis. Investigators conducted a directed content analysis. Results. The most commonly cited barriers to participation were a lack of perceived need and a sense of distrust toward the program and its staff. The most commonly cited benefits were psychosocial support and goal setting. Conclusion. Care management programs may benefit from changes to how insurance plan members are selected for the program and from adjusting program content to address perceived needs among members.

Purpose. To determine if two widely used behavioral change measures—Stages of Change (SoC) and Patient Activation Measure (PAM)—correlate with each other, are affected by financial incentives, or predict positive outcomes in the context of incentive-based health interventions. Design. Secondary analysis of two randomized controlled trials of incentives for weight loss and for improved diabetes self-monitoring. Setting. Philadelphia, Pennsylvania; Newark, New Jersey. Subjects. A total of 132 obese and 75 diabetic adults enrolled in one of two trials. Measures. SoC and PAM scores; weight loss and usage rate of diabetes self-monitoring equipment. Analysis. Multiple regression; Kruskal-Wallis test. Results. We found no association between baseline SoC and PAM scores in either study (p = .30 and p = .89). Regression models showed no association between baseline PAM score and SoC and subsequent outcomes for either study (weight loss study: PAM: p = .14, SoC: p = .1; diabetes study: PAM: p = .45, SoC: p = .61). Change in PAM score and SoC among participants in the intervention groups did not differ by study arm or among participants with better outcomes. Conclusion. PAM score and SoC may not effectively predict success or monitor progress among individuals enrolled in incentive-based interventions.

Objective. To evaluate the use of behavioral economics to design financial incentives to promote health behavior change and to explore associations with demographic characteristics. Data Source. Studies performed by the Center for Health Incentives and Behavioral Economics at the University of Pennsylvania published between January 2006 and March 2014. Study Inclusion and Exclusion Criteria. Randomized, controlled trials with available participant-level data. Studies that did not use financial incentives to promote health behavior change were excluded. Data Extraction. Participant-level data from seven studies were pooled. Data Synthesis. Meta-analysis on the pooled sample using a random-effects model with interaction terms to examine treatment effects and whether they varied by incentive structure or demographic characteristics. Results. The pooled study sample comprised 1403 participants, of whom 35% were female, 70% were white, 24% were black, and the mean age was 48 years (standard deviation 11.2 years). In the fully adjusted model, participants offered financial incentives had higher odds of behavior change (odds ratio [OR]: 3.96; p < .01) when compared to control. There were no significant interactions between financial incentives and gender, age, race, income, or education. When further adjusting for incentive structure, blacks had higher odds than whites of achieving behavior change (OR: 1.67; p< .05) with a conditional payment. Compared to lower-income participants, higher-income participants had lower odds of behavior change (OR: 0.46; p = .01) with a regret lottery. Conclusion. Financial incentives designed using concepts from behavioral economics were effective for promoting health behavior change. There were no large and consistent relationships between the effectiveness of financial incentives and observable demographic characteristics. Second-order examinations of incentive structure suggest potential relationships among the effectiveness of financial incentives, incentive structure, and the demographic characteristics of race and income.

In the coming years, assessing the impact of efforts to reduce hospital readmissions will be important to policy makers and hospitals. To inform such assessments, we sought to define preexisting trends in readmission rates for patients by level of clinical severity using a difference-in-differences analysis of Medicare inpatient claims data from 1997, 2002, and 2007 for patients with acute myocardial infarction and congestive heart failure. We also examined trends in length of stay, in-hospital mortality, and postdischarge mortality by severity level to provide additional context for interpreting readmission rate trends. From 1997 to 2007, the difference in readmission rates between the highest and lowest severity quartiles increased. Length of stay and in-hospital mortality decreased for all patients; however, postdischarge mortality increased for the highest-severity patients and decreased for the lowest-severity patients. Assessments of recent policy reforms and quality improvement programs should account for underlying differential trends in readmission rates based on patient severity.

Quality of care may be linked to the profitability of admissions in addition to level of reimbursement. Prior policy reforms reduced payments that differentially affected the average profitability of various admission types. The authors estimated a Cox competing risks model, controlling for the simultaneous risk of mortality post discharge, to determine whether the average profitability of hospital service lines to which a patient was admitted was associated with the likelihood of readmission within 30 days. The sample included 12,705,933 Medicare Fee for Service discharges from 2,438 general acute care hospitals during 1997, 2001, and 2005. There was no evidence of an association between changes in average service line profitability and changes in readmission risk, even when controlling for risk of mortality. These findings are reassuring in that the profitability of patients' admissions did not affect readmission rates, and together with other evidence may suggest that readmissions are not an unambiguous quality indicator for in-hospital care.

Purpose: To determine whether different financial incentives are effective in promoting weight loss among prediabetic Medicaid recipients. Design: Four-group, multicenter, randomized clinical trial. Setting and Participants: Medicaid managed care enrollees residing in New York, aged 18 to 64 years, and diagnosed as prediabetic or high risk for diabetes (N = 703). Intervention: In a 16-week program, participants were randomly assigned to one of 4 arms: (1) control (no incentives), (2) process incentives for attending weekly Diabetes Prevention Program sessions, (3) outcome incentives for achieving weekly weight loss goals, and (4) combined process and outcome incentives. Measures: Weight loss over a 16-week period; proportion who completed educational sessions; proportion who met weight loss goals. Analysis and Results: No intervention arm achieved greater reduction in weight than control (outcome incentive −6.6 lb [−9.1 to −4.1 lb], process incentive −7.3 lb [−9.5 to −5.1 lb], combined incentive −5.8 lb [−8.8 to −2.8 lb], control −7.9 lb [−11.1 to −4.7 lb]; all P > .29). Session attendance in the process incentive arm (50%) was significantly higher than control (31%; P < .0001) and combined incentive arms (28%; P < .0001), but not significantly higher than the outcome incentive arm (38%). Conclusion: Process incentives increased session attendance, but when combined at half strength with outcome incentives did not achieve that effect. There were no significant effects of either process or outcomes incentives on weight loss.

Purpose:To identify whether financial incentives promote improved disease management in Medicaid recipients diagnosed with hypertension or diabetes, respectively.Design:Four-group, multicenter, randomized clinical trials.Setting and Participants:Between 2013 and 2016, New York State Medicaid managed care members diagnosed with hypertension (N = 920) or with diabetes (N = 959).Intervention:Participants in each 6-month trial were randomly assigned to 1 of 4 arms: (1) process incentives—earned by attending primary care visits and/or receiving prescription medication refills, (2) outcome incentives—earned by reducing systolic blood pressure (hypertension) or hemoglobin A1c(HbA1c; diabetes) levels, (3) combined process and outcome incentives, and (4) control (no incentives).Measures:Systolic blood pressure (hypertension) and HbA1c(diabetes) levels, primary care visits, and medication prescription refills.Analysis and Results:At 6 months, there were no statistically significant differences between intervention arms and the control arm in the change in systolic blood pressure, P = .531. Similarly, there were no significant differences in blood glucose control (HbA1c) between the intervention arms and control after 6 months, P = .939. The majority of participants had acceptable systolic blood pressure (<140 mm Hg) or blood glucose (<8.0%) levels at baseline and throughout the study.Conclusion:Financial incentives—regardless of whether they were delivered based on disease-relevant outcomes, process activities, or a combination of the two—have a negligible impact on health outcomes for Medicaid recipients diagnosed with either hypertension or diabetes in 2 studies in which, among other design and operational limitations, the majority of recipients had relatively well-controlled diseases at the time of enrollment.

Purpose: To test whether employer matching of employees' monetary contributions increases employees' (1) participation in deposit contracts to promote weight loss and (2) weight loss. Design: A 36-week randomized trial. Setting: Large employer in the northeast United States. Participants: One hundred thirty-two obese employees. Interventions: Over 24 weeks, participants were asked to lose 24 pounds and randomized to monthly weigh-ins or daily weigh-ins with monthly opportunities to deposit $1 to $3 per day that was not matched, matched 1:1, or matched 2:1. Deposits and matched funds were returned to participants for each day they were below their goal weight. Measures: Rates of making ≥1 deposit, weight loss at 24 weeks (primary outcome), and 36 weeks. Analysis: Deposit rates were compared using χ2 tests. Weight loss was compared using t tests. Results: Among participants eligible to make deposits, 29% made ≥1 deposit and matching did not increase participation. At 24 weeks, control participants gained an average of 1.0 pound, whereas 1:1 match participants lost an average of 5.3 pounds ( P = .005). After 36 weeks, control participants gained an average of 2.1 pounds, whereas no match participants lost an average of 5.1 pounds ( P = .008). Conclusion: Participation in deposit contracts to promote weight loss was low, and matching deposits did not increase participation. For deposit contracts to impact population health, ongoing participation will need to be higher.

While financial incentives to providers or patients are increasingly common as a quality improvement strategy, their impact on patient subgroups and health care disparities is unclear. To examine these patterns, we analyzed data from a randomized clinical trial of financial incentives to lower low-density lipoprotein (LDL) cholesterol levels in patients at risk for cardiovascular disease. Patients with higher baseline LDL experienced greater cholesterol reductions in the shared incentive arm (0.23 mg/dL per unit change in baseline LDL, 95% CI [−0.46, −0.00]) but were also less likely to have medication potency increases in the physician incentive arm ( OR = 0.98, 95% CI [0.97, 0.996]). Uninsured patients and those of race other than Black or White were less likely to have potency increases in the shared incentive arm ( OR = 0.15, 95% CI [0.03, 0.70] and OR = 0.09, 95% CI [0.01, 0.93], respectively). These findings suggest some differential response to incentives, particularly in the form of targeted medication changes.